The present invention relates generally to energy efficiency across the data center, and more particularly to the migration of data based on power consumption.
Energy efficiency across the entire data center is becoming a top concern for corporations around the world. This problem requires consideration of all energy efficiency components of the data center, from component levels through server and system levels, and concluding with the complete data center. At the system level, storage devices are an extremely important part of the equation, which needs to be analyzed. Disk systems can require substantial amounts of power to operate and cool, and in many cases, can require more power than the server itself.
Data migration is the process of transferring data between storage types, formats or computer systems. Data migration is usually performed programmatically to achieve an automated migration, freeing up human resources from tedious tasks. It is required when organizations or individuals change computer systems or upgrade to new systems, or when systems merge (such as when the organizations that use them undergo a merger/takeover).
To achieve an effective data migration procedure, data on the old system is mapped to the new system providing a design for data extraction and data loading. The design relates old data formats to the new system's formats and requirements. Programmatic data migration may involve many phases but it minimally includes data extraction where data is read from the old system and data loading where data is written to the new system.
After loading into the new system, results are subjected to data verification to determine that data was accurately translated, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss. Automated and manual data cleansing is commonly performed in migration to improve data quality, eliminate redundant or obsolete information, and match the requirements of the new system. Data migration phases (design, extraction, cleansing, load, verification) for applications of moderate to high complexity are commonly repeated several times before the new system is activated.
Traditional data migration involves business decisions from application owners and IT administrators to predefine a destination database that usually resides physically on another disk for each given source database. Very often, such migration is a one to one relationship where a source database is mapped to a predefined destination database. This migration process is done at a database level that involves no concerns on how data is being used by applications and how it relates to power consumption.
Reference is made to FIG. 1, which illustrates a traditional database migration process 10. Traditional data migration involves moving all the data from one location to another. It is usually a one to one mapping from the source location to the destination location. Database A at 12 is a source database. A migration tool 14 manages the migration of Database A to its destination location 16. Cleansing scripts are applied to the data in Database A and data from Database A is migrated to a destination database 16. The data from Database A must be merged with any existing data on destination database 16. In these prior art methods, the destination database is predefined for each source database, not taking into account the amount of power used in the destination database and other parameters that may affect the storage and retrieval of the data after it is moved.
It is a primary object of the invention to provide a method and system for migrating data based on power conservation. It is another object of the invention to provide a method and system for selecting the destination database based on energy efficiency. It is a further object of the invention to provide a method and system for determining the length of time for realizing cost savings after migration of data has been performed.